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ICC
2009
IEEE
143views Communications» more  ICC 2009»
14 years 2 months ago
Low Complexity Markov Chain Monte Carlo Detector for Channels with Intersymbol Interference
— In this paper, we propose a novel low complexity soft-in soft-out (SISO) equalizer using the Markov chain Monte Carlo (MCMC) technique. Direct application of MCMC to SISO equal...
Ronghui Peng, Rong-Rong Chen, Behrouz Farhang-Boro...
TSP
2010
13 years 2 months ago
Markov chain monte carlo detectors for channels with intersymbol interference
In this paper, we propose novel low-complexity soft-in soft-out (SISO) equalizers using the Markov chain Monte Carlo (MCMC) technique. We develop a bitwise MCMC equalizer (b-MCMC) ...
Ronghui Peng, Rong-Rong Chen, Behrouz Farhang-Boro...
LICS
2009
IEEE
14 years 2 months ago
Statistic Analysis for Probabilistic Processes
—We associate a statistical vector to a trace and a geometrical embedding to a Markov Decision Process, based on a distance on words, and study basic Membership and Equivalence p...
Michel de Rougemont, Mathieu Tracol
ICML
2008
IEEE
14 years 8 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
CORR
2011
Springer
168views Education» more  CORR 2011»
13 years 2 months ago
Limit Theorems for the Sample Entropy of Hidden Markov Chains
The Shannon-McMillan-Breiman theorem asserts that the sample entropy of a stationary and ergodic stochastic process converges to the entropy rate of the same process almost surely...
Guangyue Han